Identification of origin place for Astragali Radix based on biomimetics
Objective To construct the origin identification model of the roots of Astragalus membranaceus var.mongholicus based on biomimetics and back propagation neural network(BPNN).Methods Totally 21 indicators were measured by colorimeter,electronic nose(E-nose),and electronic tongue(E-tongue).Totally 14 indicators were obtained by random forest importance(RFI)after feature screening,and AR origin identification was modeled as a multi-classification problem.By comparing the three machine learning models(RF,SVM,and BPNN),a decision system was built for classification based on BPNN.Results BPNN well predicted the geographical origins of AR with only 11 feature variables.After constructing the multi-classification model,SHapley Additive exPlanation(SHAP)values were introduced to interpret the constructed origin identification model.Conclusion The importance ranking of the SHAP features shows how important the variables are in the actual model.Interpretable prediction models increase the transparency of the origin prediction model while maintaining the discrimination correctness of the original model.This study provides some reference for the construction of origin identification models.
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